Dynamic liquid crystal elastomers (DLCEs) are a class of stimuli-responsive materials characterized by their unique optical and thermomechanical properties. These are lightly crosslinked polymer networks with covalently bonded mesogens, which result in materials with mechanical properties of elastomers while retaining the anisotropy of small molecule liquid crystals. In this project, we are studying polydomain DLCEs as potential pluripotent materials that have the ability to reorganize their constituent units in response to different macroscopic mechanical deformation processes (or training), to allow access to a range of materials with different properties/functionalities. Here, we are investigating how the different training/processing protocols, the type of dynamic bonds, and the nature of the LC network influence the alignment of mesogens, which consequently determines the resulting properties/functionalities in DLCEs. By varying the crosslink density of the system and the amount of liquid crystalline component, we can tune the packing arrangement of mesogens, which will allow us to control the energy stored in the network. Therefore, we plan to leverage mesogen templated ordering with stress relaxation induced by the dynamic exchange to post-synthetically modify the functional response in DLCEs.

Trainable soft materials using dynamic liquid crystal elastomers

Fall 2022 abstracts, posters, and presentations will launch in mid-September.

ACS Fall 2022

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.